Which dimensionality reduction technique can also be used as a feature extraction method, transforming the data into a set of linearly uncorrelated variables?
- Principal Component Analysis (PCA)
- Independent Component Analysis (ICA)
- t-SNE (t-distributed Stochastic Neighbor Embedding)
- Autoencoders
Independent Component Analysis (ICA) is a dimensionality reduction technique that can also extract independent and linearly uncorrelated features from data. ICA is especially useful when dealing with non-Gaussian data and is a powerful tool in signal processing and blind source separation.
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